PhD of Computer Science / Numerical Algorithms – Københavns Universitet

Videresend til en ven Resize Print kalender-ikon Bookmark and Share

Datalogisk Institut, DIKU > Om DIKU > Ledige stillinger > PhD of Computer Scienc...

PhD of Computer Science / Numerical Algorithms

DIKU seeks applications for a PhD position position for development of high performance numerical algorithms for applications in real-time analysis of electric power systems.

Numerical algorithms for power system applications is a field with multiple unexplored areas offering exciting challenges for algorithm experts and possibility for high-impact publications and high-impact applications in an important applied field.

The candidate will work with assistant professor Stefan Sommer at DIKU and be part of the Danish SARP project (Security Assessment of Renewable Power Systems) funded by the ForskEL 2016 research programme and lead by DTU Centre for Electrical Engineering (CEE) in cooperation with DTU Wind Energy and Department of Computer Science, UCPH. The employment period will be 3 years.

As the share of variable renewable energy generation like wind and solar PV is steadily growing in power systems, the issue of ensuring continued secure power system operation becomes increasingly challenging. An important condition for assuring stable and secure power system operation is the presence of high performance algorithms for analysis of the power system state. In order to pursue real-time security assessment and operation, efficient algorithms ensuring fast execution must be developed. Focus is on identifying computationally critical parts for the stability algorithms, developing effective algorithms that provide speedup in execution, e.g. allowing parallelization of computationally intensive parts, and exploiting graph theoretical properties of the power networks. Mathematical modeling and understanding of the mathematical structure of the problem is important. Examples of relevant algorithm paradigms are sparse algorithmssparse matrix factorization (e.g. sparse LU-factorization), parallel execution of structured linear algebra algorithms, and massively parallel numerical algorithms.

Qualifications

The successful candidate is required to have the following qualifications:

  • MSc degree (or equivalent) in Computer Science, Mathematics, Physics, Statistics, Engineering or other relevant fields;
  • experience with use of numerical algorithms;
  • experience with some of the following fields (e.g. courses or project work): mathematical modeling, data analysis, graph theory, numerical analysis, parallel or high-performance computing;
  • ability to work in a project team and take responsibility for own research goals;
  • ability to communicate, read and write in English.

Duties will include:

  • manage and carry out your own research project;
  • attain 30 ECTS in PhD-level courses;
  • write scientific articles and your PhD thesis;
  • participate in international conferences;
  • stay at a research institution abroad for a few months;
  • teach and disseminate your research;
  • work for the department in duties such as teaching assistantships.

Further information on the Department is linked at http://www.science.ku.dk/english/about-the-faculty/departments/. Inquiries about the position can be made to Stefan Sommer (sommer@di.ku.dk/+45 21179125).

The position is open from 1 March 2017 or as soon as possible thereafter.

The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.

The successful candidate will be requested to formally apply for enrollment as a PhD student at the PhD school of Science.

General information about PhD programmes at SCIENCE is available at http://www.science.ku.dk/phd

Submission of application

The deadline for applications is 29 January 2017, 23:59 GMT +1. The application, in English, must be submitted electronically by clicking APPLY NOW.

Please include 

  • motivated letter of application;
  • statement of research interests;
  • curriculum vita;
  • diplomas (Master degree or equivalent)
  • complete publication list, if any;
  • copy of master’s thesis;
  • separate reprints of up to 3 particularly relevant papers, if any.

Appointment procedure

After the application deadline, the Head of Department selects applicants for assessment on the advice of the Appointment Committee. All applicants are then immediately notified whether their application has been accepted for assessment. The Dean subsequently appoints an expert assessment committee tasked with carrying out an assessment of the selected applicants for the specific post. Selected applicants are notified of the composition of the committee. Applicants are ultimately offered the opportunity of commenting on the part of the assessment relating to themselves before the appointment is finalized.

You can read about the recruitment process at http://employment.ku.dk/faculty/recruitment-process/.

Terms of employment and salary

The position is covered by the Memorandum on Job Structure for Academic Staff. Terms of appointment and payment accord to the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State. The starting salary is currently at a minimum DKK 305,291 including annual supplement (+ pension up to DKK 42,171).

If you consider applying from abroad, you may find useful information on how it is to work in Denmark and at UCPH. See: http://ism.ku.dkhttp://www.nyidanmark.dk/en-us/frontpage.htm and https://www.workindenmark.dk/

APPLY NOW

Part of the International Alliance of Research Universities (IARU), and among Europe’s top-ranking universities, the University of Copenhagen promotes research and teaching of the highest international standard. Rich in tradition and modern in outlook, the University gives students and staff the opportunity to cultivate their talent in an ambitious and informal environment. An effective organisation – with good working conditions and a collaborative work culture – creates the ideal framework for a successful academic career.